Noise suppression for detection and location of microseismic events using a matched filter

ABSTRACT

A method for determining presence of seismic events in seismic signals includes determining presence of at least one seismic event in seismic signals corresponding to each of a plurality of seismic sensors. A correlation window is selected for each of the plurality of seismic signals. Each correlation window has a selected time interval including an arrival time of the at least one seismic event in each seismic signal. Each window is correlated to the respective seismic signal between a first selected time and a second selected time. Presence of at least one other seismic event in the seismic signals from a result of the correlating.

CROSS-REFERENCE TO RELATED APPLICATIONS

Not applicable.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The invention relates generally to the field of imaging the Earth'ssubsurface using passive seismic detection techniques. Morespecifically, the invention relates to processing methods for passiveseismic signals to improve the ability to detect subsurface seismicevents from such signals.

2. Background Art

Passive seismic emission tomography is a process in which an array ofseismic sensors is deployed in a selected pattern on or near the Earth'ssurface (or on or near the water bottom in marine surveys and inwellbores drilled through subsurface formations) and seismic energy isdetected at the sensors that emanates from various seismic eventsoccurring within the Earth's subsurface. Processing the signals detectedby the sensors is used to determine, among other things, the position inthe Earth's subsurface and the time at which the various seismic eventstook place.

Applications for passive seismic emission tomography include, forexample, determining the point of origin of microearthquakes caused bymovement along geologic faults (breaks in rock layers or formations),movement of fluid in subsurface reservoirs, activation of naturalfaults, casing failure, reservoir compaction, sealing faults, andmonitoring of movement of proppant-filled fluid injected into subsurfacereservoirs to increase the effective wellbore radius of wellboresdrilled through hydrocarbon-producing subsurface Earth formations(“fracturing”). The latter application, known as “frac monitoring” isintended to enable the wellbore operator to determine, with respect totime, the direction and velocity at which the proppant filled fluidmoves through particular subsurface Earth formations.

Passive seismic emission tomography for the above types ofinterpretation includes determining what are seismic-induced events fromwithin the signals detected at each of the seismic sensors, and for eachevent detected at the seismic sensors, determining the spatial positionand time of the origin of the seismic event. Passive seismicinterpretation methods known in the art are undergoing continuousimprovement to better resolve the source of seismic events originatingfrom the Earth's subsurface. There continues to be a need for improvedmethods of passive seismic emission tomography.

SUMMARY OF THE INVENTION

A method for determining presence of seismic events in seismic signalsaccording to one aspect of the invention includes determining presenceof at least one seismic event in seismic signals corresponding to eachof a plurality of seismic sensors. A correlation window is selected foreach of the plurality of seismic signals. Each correlation window has aselected time interval including an arrival time of the at least oneseismic event in each seismic signal. Each window is correlated to therespective seismic signal between a first selected time and a secondselected time. Presence of at least one other seismic event in theseismic signals from a result of the correlating.

Other aspects and advantages of the invention will be apparent from thefollowing description and the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an example array of seismic sensors disposed above aportion of the subsurface to be surveyed using passive seismic signals.

FIG. 2A shows an example of a master seismic event in passive seismicsignals.

FIG. 2B shows an example of the data in FIG. 2A subjected to filtering.

FIG. 3 shows an example of slave events detected in the data of FIG. 2Ausing a cross-correlation technique according to the invention.

FIG. 4 shows a flow chart of an example process according to theinvention.

DETAILED DESCRIPTION

In methods according to the invention, seismic events originating in theEarth's subsurface may be identified and their spatial origin and timeof origin may be determined. Such seismic events may be naturallyoccurring, or may be induced by performing certain activities onsubsurface formations. Recording seismic signals related to suchsubsurface origin seismic events is known as “passive” seismicsurveying.

Passive seismic signals may be acquired for processing according to theinvention using an array of seismic sensors such as shown in FIG. 1. Thearray shown in FIG. 1 generally at 10 includes radially extending lines11 through 20 of spaced apart seismic sensors, individual examples ofwhich are shown at 22, such as single component or multi-componentgeophones, accelerometers or other particle motion sensors. The array 10shown in FIG. 1 is configured and used, in some examples, as part of afracture monitoring service sold under the trademark FRACSTAR, which isa registered trademark of Microseismic, Inc., Houston, Tex., theassignee of the present invention. In such monitoring service, seismicsignals are detected while fluid is pumped into a subsurface formationfrom the surface through a wellbore W drilled through the subsurfaceformations. See, for example, U.S. Patent Application Publication No.2008/0068928 filed by Duncan et al., and the patent application forwhich is assigned to the assignee of the present invention for adescription of fracture monitoring using passive seismic signals.

The arrangement of the array 10 shown in FIG. 1, however, is only oneexample of an arrangement of seismic sensors that may be used to acquirepassive seismic signals according to the invention, and such arrangementshould not be construed as a limit on the scope of the presentinvention. The invention is also not limited in scope to use withfracture monitoring, but may be used with any type of passive seismicsurveying. For example, seismic surveys according to the invention maybe conducted on land or on the bottom of a body of water. Surveys mayalso be conducted with seismic sensors deployed in a wellbore drilledthrough subsurface formations or a mine. If an array of seismic sensorsis disposed on the bottom of a body of water, for example, the seismicsensors may include or be substituted by hydrophones or similar sensorthat is responsive to pressure or the time gradient of pressure.Wellbore sensors may include either or both particle motion responsivesensors and pressure responsive sensors. See, for example, U.S. Pat. No.4,715,469 issued to Yasuda et al. for an example of a wellbore sensorsystem.

A recording system 21 disposed proximate the array 10 may includeequipment for (not shown separately) to be used to record the signalsgenerated by the seismic sensors in each of the sensor lines 11-20. Thesignals may be recorded individually for each sensor 22, or in someexamples, selected numbers of adjacent seismic sensors in each line11-20 may have their signals combined or summed by electrical seriesconnection or other electrical configuration, or the signals may beequivalently summed in the recording system 21. The recording system 21may include a general purpose, programmable computer (not shownseparately) for processing the recorded signals, including according tothe invention. Processing signal recordings according to the inventionmay be also performed at any other location.

Recording seismic signals generated by the sensors 22 in the array 10may be performed continuously over a selected period of time, forexample from several minutes to several weeks in duration. In otherexamples, signal recording may take place over a time period extendingas long as several years in duration. Thus, for each sensor (or selectedgroups of sensors) a signal recording will include signal amplitude withrespect to time for the entire selected recording time interval.

In a method according to the invention, all or a selected subset of therecorded seismic signals may be scanned to detect one or more eventsthat may be reasonably inferred to be of seismic origin. Such scanningmay include identifying signal amplitudes in the recorded signals that,for example, exceed a selected threshold (amplitude peaks). When one ormore of such events are detected in a plurality of the recorded signals,the time of arrival of each such event in each recorded signal isdetermined in order to establish that the events are possibly of seismicorigin. One technique for determining whether the identified amplitudepeaks may be of seismic origin is to determine whether the arrival timesof such peaks at each seismic sensor correspond to normal moveout, whichis a relationship between event arrival time at the sensors and distancefrom the source of the event and the particular sensor that detected theseismic energy from the event. As will be appreciated by those skilledin the art, determining whether the event arrival times correspond tonormal moveout will depend in part on the spatial distribution ofseismic velocity in the subsurface and the positions of the seismicsensors 22.

Once a particular event has been so identified in the seismic signals,it may be characterized for purposes of the method as a “master” seismicevent. For each such master seismic event, a selected correlation“window” may be established. Typically such correlation window will be atime subset of the recorded seismic signals from each sensor, typicallywithin a time interval on the order of one to three hundred millisecondsduration, and such window may be centered in time at the time of theamplitude peak identified as a master seismic event. Thus, thecorrelation window may contain a portion of the recorded seismic signalfrom about 50 milliseconds to 150 milliseconds before the amplitudepeak, the amplitude peak, and between 50 milliseconds and 150milliseconds of recorded seismic signal after the amplitude peak. Thetime window lengths may wary according to the duration of the seismicsignal observed in the particular set of recorded seismic signals.

The foregoing correlation window is then correlated with the seismicsensor signal recording from which it was taken. Correlation using thecorrelation window may begin at a first selected time and may end at asecond selected time. The first and second selected times may correspondto the beginning and end of signal recording for the particular seismicsensor signal, or they may correspond to one or more time subsets of theentire recorded signal. An output of the correlation will be anamplitude, with respect to time, that represents the degree ofsimilarity between the signals in the correlation window and acorresponding signal to noise ratio in the selected time windows of therecoded signals. Time values for the correlation output will be within arange beginning at the peak arrival recording time less the firstselected time, extending to the peak arrival time less the secondarrival time.

The foregoing correlation procedure may then be repeated for the masterseismic event identified in others of the recorded signals. Note thateach correlation is performed by selecting a correlation window fromeach selected recorded signal, and applying the respective correlationwindow to the recorded signal from which the window was selected. In thecase of multi-component geophones used as the sensors, the correlationshould be performed using a correlation window taken from the signalrecording of the particular component signal being processed. Processingthe seismic signals by such correlation will improve the ability toidentify “slave seismic events”, meaning those seismic events that areclosely related to the master event in spatial origin and mechanism bywhich the seismic event is generated.

The result of the correlation may remove phase character of the masterseismic event that affects slave seismic events in the same recordedsignal, thus increasing the signal to noise ratio of the slave seismicevents in the recorded seismic signal. The correlation may also reducethe effect of time moveout of the seismic signal between the spatialorigin of the seismic event and each sensor in the array. Correlationmay also reduce the effect of the nature of the seismic source energyand the effects of the geologic formations between the source and eachparticular receiver (referred to as the Earth filter). Examples ofperforming the above procedure will be further explained below withreference to FIGS. 2A, 2B and 3.

An explanation of the theory of processing seismic signals as explainedabove follows. The particular explanation is related to particle motionseismic sensors, however the general principle is applicable to othertypes of seismic sensors. Seismic data observed at any seismic sensorcan be described as a convolution of the particle motion of the seismicsource, the seismic response (including transmission characteristics ofthe media through which the seismic energy travels from the source tothe sensor), and the seismic sensor response to imparted particlemotion. Such convolution may be represented by the expression:

D(t)=S(t)

G(t)

R(t)  (1)

in which t is time, D(t) is the seismic data observed or recorded withrespect to time, S(t) is the seismic energy source characteristic withrespect to time, G(t) is medium or subsurface response (which may be thelinear sum of Green's functions), R(t) is sensor response function and

represents convolution in the time domain. Note that the sourcefunction, S(t) and the subsurface response G(t) are tensors of thesecond and fourth order, and that equation (1) represents a dyadicproduct of these two tensors.

In passive seismic signal measuring it can be assumed that the seismicenergy source characteristic with respect to time S(t) is a deltafunction. Furthermore, for seismic events in the subsurface thatoriginate relatively near to each other with respect to the distancebetween the origin of such events and the sensor positions (called“spatially related” seismic events), and for subsets of the seismicsensors that are relatively closely spaced to each other, the sensorresponse function R(t) and the media response function (Earth filter)G(t) are similar for such events and such sensors. Finally, if theseismic energy source mechanisms for discrete seismic events are similarto each other (events being “related in mechanism of origin”), thesource function S in equation (1) may be characterized as producing twosimilar time dependent waveforms:

D ₁(t)=S ₁ ·G ₁

R₁(t)≈D₂(t+τ)=S ₂ ·G ₂(t+Σ)

R₂(t+τ)  (2)

where τ is the time delay between seismic events 1 and 2, and theparameter subscripts in equation (2) indicate the respective seismicevents. To use equation (2) it is possible to cross-correlate recordedseismic signals corresponding to what may be identified as a “master”seismic event in the recorded seismic signals. Such cross correlationmay provide a good signal-to-noise ratio estimate of D₁ even in noisyrecordings. If signals from a second or further seismic event thatsatisfies equation (2) are present in such recordings, cross-correlationof two similar signals using the window technique explained above willgenerate a high correlation result for such second or further seismicevents, and such result may be identified as one or more “slave” seismicevents. However, if the recordings contain only noise or seismic eventswith different fundamental characteristics, then the correlation resultwill be relatively low, especially if stacked over many receivers (i.e.very many realizations of random cross-correlation coefficient).Furthermore, if equation (2) is satisfied, the correlation function willhave a peak value at nearly the same time in all sensors in the sensorconfiguration. Thus, a high value of stacked crosscorrelation from allsensors indicates detection of a slave seismic event, similar to amaster seismic event. Such events are also known as “doublets” inearthquake seismology.

A correlation of two similar signals enhances the signal-to-noise ratioof the scattered energy. The seismic source energy is scattered over atime window by the medium (Earth filter) response and the sensorresponse (G(t) and R(t) in equation (1)). Correlation of master andslave seismic events that satisfy equation (2) represents a sum ofsquares of the scattered arrivals all contributing to the peak amplitudeof the correlation coefficient. The correlation as described above is ascalar product of the time vectors between the window centered aroundthe master seismic event and the window taken from the continuousseismic signal sample.

The above technique has been applied to data from a hydraulic fracturemonitoring procedure where the hydraulic fracture was stimulated inseveral stages of horizontal treatment in a well at a depth ofapproximately 12,000 ft (3,600 m). Six stages of slurry with a proppantwere injected into a shale formation. The present example investigatedthe initial 15 minutes of the final, sixth stage of slurry pumping,which reactivated a previously stimulated part of a low permeabilitysubsurface gas reservoir. It was possible to detect and locate severalhundred seismic events with the stacking of 935 receivers above thereservoir in the vicinity of an injection point close to the left mostline 20 of sensors shown in FIG. 1. Initially, one strong master seismicevent was observed during the first 15 minutes of fracturing. FIGS. 2Aand 2B show waveforms of recorded signals processed using noisesuppression of the strongest events detected during stage 6 of thepreviously described hydraulic fracture stimulation. Note that thewaveforms show long reverberations, believed to be caused by energy pathand receiver effects, and which last at least 0.4 seconds. Also notethat a first signal arrival, shown at 24, is relatively impulsive,indicating a sharp onset of a master event. The move-out shown in thesignals is consistent with a seismic source located at approximately thedepth of the fracture fluid injection (i.e. 12,000 ft).

Because the signal-to-noise appears relatively good for this “master”event, it may be identified as a master event (D₁) in equation (2).Next, the signals were processed by cross-correlating a 0.4 second (400millisecond) time window centered around the master event over theentire 15 minutes of data recorded during the fracture monitoringprocedure. FIG. 3 shows the cross-correlations of the master event ofFIG. 2A with 3 seconds of the time windows around the slave events(e.g., at 26) shown in FIG. 2B. Note the high correlation for the timesaround 828.5 and 829.6 seconds. These high cross-correlations correspondto two strong slave seismic events, 28 and 30, that are barely visiblein FIG. 2B. Note that there is virtually no move-out of the peak of thecross-correlations in FIG. 3 because the spatial origin of the masterevent and the slave events are essentially the same. It should be notedthat the cross-correlations shown in FIG. 3 removed the move-out withoutany knowledge of the velocity structure, just by satisfying equation(2). If there is move-out in any identified slave events, it can befurther used by stacking the cross-correlations for different move-outseach of which corresponds to a different location of the origin of suchslave events. The location with highest stacked cross correlation may beused to identify the point of origin of a slave event.

To find all slave events which correlate with negligible move-out(negligible relative to the sample time interval of 0.004 sec), it ispossible then to stack the correlated traces for the signals wherein themaster event has a good signal-to-noise ratio. Stacking additionalsignals further improves detection of weak events as long as the masterevent has a good signal-to-noise ratio on the respective data traces.

After master and slave events have been identified as explained above,the spatial origin (and time of origin) of each such event may bedetermined. One technique for determining origin of seismic events inpassive seismic signals is described in U.S. Patent ApplicationPublication No. 2008/0068928 filed by Duncan et al., and the patentapplication for which is assigned to the assignee of the presentinvention. Another technique for determining spatial origin is calledtravel time tomography. One such technique is described in, W. H. K. Leeand S. W. Stewart, Principles and Applications of MicroearthquakeNetworks, Advances in Geophysics, Supplement 2, Academic Press (1981).

FIG. 4 shows a flow chart of an example process. At 40, signalrecordings (traces) from selected ones of the sensors, and/or summedgroups thereof are scanned to identify master events at 42. As explainedabove, identification of master events may include detection of eventsabove a selected amplitude threshold that satisfy normal moveout. At 44,a correlation window is selected for each signal or trace to beprocessed. At 46, the correlation window is correlated with the datatrace from which the window is selected. Such correlation may beperformed on selected traces or all available traces in a data set. At48, slave events may be identified in the correlation output. At 50, thearrival times of the slave events in each trace may be used to identifythe spatial origin of the slave events

Methods of processing seismic signals according to the invention mayprovide better capability to identify spatially and mechanically relatedseismic events originating in the Earth's subsurface than is possibleusing processing methods known in the art prior to the presentinvention. Such identification may make possible more accurateevaluation of subsurface geologic processes, such as fluid movement insubsurface formations, detecting perforation taking place within acasing, casing collapse, and subsidence of formations caused by fluidwithdrawal as not limiting examples.

While the invention has been described with respect to a limited numberof embodiments, those skilled in the art, having benefit of thisdisclosure, will appreciate that other embodiments can be devised whichdo not depart from the scope of the invention as disclosed herein.Accordingly, the scope of the invention should be limited only by theattached claims.

1. A method for determining presence of seismic events in seismicsignals, comprising: determining presence of at least one seismic eventin seismic signals corresponding to each of a plurality of seismicsensors; selecting a correlation window from each of the plurality ofseismic signals, each correlation window having a selected time intervalincluding an arrival time of the at least one seismic event in eachseismic signal; correlating each window to the respective seismic signalbetween a first selected time and a second selected time; anddetermining presence of at least one other seismic event in the seismicsignals from a result of the correlating.
 2. The method of claim 1wherein the determining presence of the at least one seismic eventcomprises selecting signal amplitude above a selected threshold in eachof the seismic signals and determining whether arrival time of eventsabove the selected threshold correspond to normal moveout of seismicenergy.
 3. The method of claim 1 further comprising determining aspatial origin of the at least one seismic event and the at least oneother seismic event.
 4. The method of claim 1 further comprisingdetermining a time of origin of the at least one seismic event and theat least one other seismic event.
 5. The method of claim 1 wherein theat least one seismic event and the at least one other seismic event arespatially related.
 6. The method of claim 1 wherein the at least oneseismic event and the at least one other seismic event are related inmechanism of origin.
 7. The method of claim 1 wherein the seismicsignals are acquired from an array of seismic sensors deployed near theEarth's surface.
 8. The method of claim 1 wherein the at least oneseismic event and the at least one other seismic event are generated bypumping fluid into a subsurface formation.
 9. A method for seismicevaluation of the Earth's subsurface, comprising: deploying a pluralityof seismic sensors proximate a volume of the Earth's subsurface to beevaluated; detecting seismic signals from each of the sensors for aselected time interval; determining presence of at least one seismicevent in the seismic signals corresponding to each of the seismicsensors; selecting a correlation window from each of the seismicsignals, each correlation window having a selected time intervalincluding an arrival time of the at least one seismic event in eachseismic signal; correlating each window to the respective seismic signalbetween a first selected time and a second selected time; anddetermining presence of at least one other seismic event in the seismicsignals from a result of the correlating.
 10. The method of claim 9wherein the determining presence of the at least one seismic eventcomprises selecting signal amplitude above a selected threshold in eachof the seismic signals and determining whether arrival time of eventsabove the selected threshold correspond to normal moveout of seismicenergy.
 11. The method of claim 9 further comprising determining aspatial origin of the at least one seismic event and the at least oneother seismic event.
 12. The method of claim 9 further comprisingdetermining a time of origin of the at least one seismic event and theat least one other seismic event.
 13. The method of claim 9 wherein theat least one seismic event and the at least one other seismic event arespatially related.
 14. The method of claim 9 wherein the at least oneseismic event and the at least one other seismic event are related inmechanism of origin.
 15. The method of claim 9 wherein the seismicsignals are acquired from an array of seismic sensor deployed near theEarth's surface.
 16. The method of claim 9 wherein the at least oneseismic event and the at least one other seismic event are generated bypumping fluid into a subsurface formation.
 17. The method of claim 9where at least one event is perforation shot.
 18. The method of claim 9wherein the at least one seismic event and the at least one otherseismic event are generated by reservoir subsidence
 19. The method ofclaim 9 wherein the at least one seismic event and the at least oneother seismic event are generated by casing failure in a subsurfaceformation.